PedGenie

PedGenie: an analysis approach for genetic association testing in extended pedigrees and genealogies of arbitrary size. Background: We present a general approach to perform association analyses in pedigrees of arbitrary size and structure, which also allows for a mixture of pedigree members and independent individuals to be analyzed together, to test genetic markers and qualitative or quantitative traits. Our software, PedGenie, uses Monte Carlo significance testing to provide a valid test for related individuals that can be applied to any test statistic, including transmission disequilibrium statistics. Single locus at a time, composite genotype tests, and haplotype analyses may all be performed. We illustrate the validity and functionality of PedGenie using simulated and real data sets. For the real data set, we evaluated the role of two tagging-single nucleotide polymorphisms (tSNPs) in the DNA repair gene, NBS1, and their association with female breast cancer in 462 cases and 572 controls selected to be BRCA1/2 mutation negative from 139 high-risk Utah breast cancer families.

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References in zbMATH (referenced in 4 articles )

Showing results 1 to 4 of 4.
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  1. Bureau, Alexandre; Duchesne, Thierry: On the validity of within-nuclear-family genetic association analysis in samples of extended families (2015)
  2. Yang, Yaning; Remmers, Elaine F.; Ogunwole, Chukwuma B.; Kastner, Daniel L.; Gregersen, Peter K.; Li, Wentian: Effective sample size: quick estimation of the effect of related samples in genetic case-control association analyses (2011)
  3. Curtin, Karen; Wong, Jathine; Allen-Brady, Kristina; Camp, Nicola J.: Pedgenie: Meta genetic association testing in mixed family and case-control designs (2007) ioport
  4. Allen-Brady, Kristina; Wong, Jathine; Camp, Nicola J.: Pedgenie: An analysis approach for genetic association testing in extended pedigrees and genealogies of arbitrary size (2006) ioport